Preventing drowning in information: a topic model approach to relating information on Strategic Scanning
Alexis Miranda Carillo, Edison Loza-Aguirre, Carlos Montenegro · 2020
Information overload lead managers to not adequately use the relevant information they collect in Strategic Scanning. Such information comes in small pieces of text that are dispersed in terms of time, language, and sources. These characteristics of information from Strategic Scanning usually prevent to identify connections with the previously collected information. In this paper, we propose an alternate tool for dealing with this issue by using topic analysis techniques. The tool provides a quick reading interface, in which the proximity relationship between various texts can be easily visualized. We compare our tool with two mechanisms for clustering and proximity measurement. Our tool excelled in terms of execution time and of the pertinence of results.